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A Novel Framework for Quantum-Enhanced Detection and Mitigation of Man-in-the-Middle Attacks on IoT Devices Using SDN

International Journal of Electrical and Electronics Engineering
© 2024 by SSRG - IJEEE Journal
Volume 11 Issue 11
Year of Publication : 2024
Authors : Yasoda Krishna Kuppili, Beera John Jaidhan
10.14445/23488379/IJEEE-V11I11P140
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How to Cite?

Yasoda Krishna Kuppili, Beera John Jaidhan, "A Novel Framework for Quantum-Enhanced Detection and Mitigation of Man-in-the-Middle Attacks on IoT Devices Using SDN," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 11, pp. 438-447, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I11P140

Abstract:

In today’s age of the Internet of Things (IoT), it is crucial to ensure that devices communicate securely. This study presents a system that uses quantum techniques in Software Defined Networking (SDN) to detect and counteract Man-in-the-Middle (MitM) attacks on devices. Our method incorporates quantum cryptography to enhance the security of SDN controllers, bolstering defense against attacks. By merging sophisticated intrusion detection algorithms with strategies, our framework enhances accuracy and response times compared to other approaches. Through simulations, we have showcased that our system adeptly identifies and thwarts MitM attacks while meeting security standards, offering a solution for safeguarding IoT networks.

Keywords:

SDN, MitM, QKD, IoT, Quantum-enhanced detection.

References:

[1] Qing Li et al., “Medical Image Classification with Convolutional Neural Network,” 13th International Conference on Control Automation Robotics & Vision (ICARCV), Singapore, pp. 844-848, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Sanaz Rahimi Moosavi et al., “SEA: A Secure and Efficient Authentication and Authorization Architecture for IoT-Based Healthcare Using Smart Gateways,” Procedia Computer Science, vol. 52, pp. 452-459, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Jie Lin et al., “A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications,” IEEE Internet of Things Journal, vol. 4, no. 5, pp. 1125-1142, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Julia Rauscher, and Bernhard Bauer, “Safety and Security Architecture Analyses Framework for the Internet of Things of Medical Devices,” IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), Ostrava, Czech Republic, pp. 1-3, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Anastasiia Strielkina et al., “Cybersecurity of Healthcare IoT-Based Systems: Regulation and Case-Oriented Assessment,” IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT), Kyiv, Ukraine, pp. 67-73, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Anastasiia Strielkina, Vyacheslav Kharchenko, and Dmytro Uzun, “Availability Models of The Healthcare Internet of Things System Taking Into Account Countermeasures Selection,” Information and Communication Technologies in Education, Research, and Industrial Applications Conference, pp. 220-242, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Jianbing Ni, Xiaodong Lin, and Xuemin Shen, “Toward Edge-Assisted Internet of Things: From Security and Efficiency Perspectives,” IEEE Network, vol. 33, no. 2, pp. 50-57, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Truong Thu Huong et al., “LocKedge: Low-Complexity Cyberattack Detection in IoT Edge Computing,” IEEE Access, vol. 9, pp. 29696-29710, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Truong Thu Huong et al., “An Efficient Low Complexity Edge-Cloud Framework for Security in IoT Networks,” IEEE Eighth International Conference on Communications and Electronics (ICCE), Phu Quoc Island, Vietnam, pp. 533-539, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Julia Rauscher, and Bernhard Bauer, “Adaptation of Architecture Analyses: An IoT Safety and Security Flaw Assessment Approach,” Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021), pp. 320-327, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Omar Cheikhrouhou et al., “A Lightweight Blockchain and Fog-enabled Secure Remote Patient Monitoring System,” Internet of Things, vol. 22, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Celestino Obua, MUST Data Science Research Hub (MUDSReH), NIH RePORTER, 2022. [Online]. Available: https://reporter.nih.gov/project-details/10312539#details
[13] Ken Hoyme, Security Safety Co-Analysis Tool Environment (SSCATE), Adventium Enterprises, SBIR STTR America’s Seed Fund, 2016. [Online]. Available: https://legacy.www.sbir.gov/sbirsearch/detail/1252209
[14] Ken Hoyme, Security Safety Co-Analysis Tool Environment (SSCATE), Adventium Enterprises, SBIR STTR America’s Seed Fund, 2015. [Online]. Available: https://legacy.www.sbir.gov/sbirsearch/detail/869241
[15] Lenore McMackin, SBIR Phase II: Low Cost Shortwave Infrared (SWIR) Spectral Imaging Microscope Camera Based on Compressive Sensing, Inview Technology Corporation, SBIR STTR America’s Seed Fund, 2014. [Online]. Available: https://legacy.www.sbir.gov/sbirsearch/detail/704773
[16] Lenore McMackin, SBIR Phase I: Low Cost Shortwave Infrared (SWIR) Spectral Imaging Microscope Camera Based on Compressive Sensing, Inview Technology Corporation, US National Science Foundation, 2013. [Online]. Available: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1315515
[17] Muhammad Yaseen et al., “MARC: A Novel Framework For Detecting MitM Attacks In EHealthcare BLE Systems,” Journal of Medical Systems, vol. 43, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Alper Kaan Sarica, and Pelin Angin, “A Novel SDN Dataset for Intrusion Detection in IoT Networks,” 16th International Conference on Network and Service Management (CNSM), Izmir, Turkey, pp. 1-5, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Miloud Bagaa et al., “A Machine Learning Security Framework for IoT Systems,” IEEE Access, vol. 8, pp. 114066-114077, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Nagarathna Ravi, and S. Mercy Shalinie, “Learning-Driven Detection and Mitigation of DDoS Attacks in IoT Via SDN-Cloud Architecture,” IEEE Internet of Things Journal, vol. 7, no. 4, pp. 3559-3570, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[21] P.K. Binu, Deepak Mohan, and E.M. Sreerag Haridas, “An SDN-Based Prototype for Dynamic Detection and Mitigation of DoS Attacks in IoT,” 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, pp. 5-10, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Tolijan Trajanovski, and Ning Zhang, “An Automated and Comprehensive Framework for IoT Botnet Detection and Analysis (IoT-BDA),” IEEE Access, vol. 9, pp. 124360-124383, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Harsh Sharma, and Shashank Gupta, “Leveraging Machine Learning and SDN-Fog Infrastructure to Mitigate Flood Attacks,” 2021 IEEE Globecom Workshops (GC Wkshps), Madrid, Spain, pp. 1-6, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Walid I. Khedr, Ameer E. Gouda, and Ehab R. Mohamed, “FMDADM: A Multi-Layer DDoS Attack Detection and Mitigation Framework Using Machine Learning for Stateful SDN-Based IoT Networks,” IEEE Access, vol. 11, pp. 28934-28954, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Rami J. Alzahrani, and Ahmed Alzahrani, “A Novel Multi Algorithm Approach to Identify Network Anomalies in The IoT Using Fog Computing and A Model to Distinguish Between IoT and Non-IoT Devices,” Journal of Sensor and Actuator Networks, vol. 12, no. 2, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Mingyuan Zang et al., “Toward Continuous Threat Defense: In-Network Traffic Analysis for IoT Gateways,” IEEE Internet of Things Journal, vol. 11, no. 6, pp. 9244-9257, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Hicham Amellal et al., “Quantum Man-in-the-Middle Attacks on QKD Protocols: Proposal of a Novel Attack Strategy,” 6th International Conference on Contemporary Computing and Informatics, Gautam Buddha Nagar, India, pp. 513-519, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Shatha Alhazmi et al., “Mitigating Man-in-the-Middle Attack Using Quantum Key Distribution,” IEEE Long Island Systems, Applications and Technology Conference, Old Westbury, NY, USA, pp. 1-6, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Abdullah Al Hayajneh, Md Zakirul Alam Bhuiyan, and Ian McAndrew, “Improving Internet of Things (IoT) Security with Software-Defined Networking (SDN),” Computers, vol. 9, no. 1, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[30] S. Aruna et al., “Detect and Prevent Attacks of Intrusion in IoT Devices Using Game Theory with Ant Colony Optimization (ACO),” Journal of Cybersecurity and Information Management, vol. 14, no. 2, pp. 275-286, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Mst Shapna Akter et al., “Quantum Cryptography for Enhanced Network Security: A Comprehensive Survey of Research, Developments, and Future Directions,” IEEE International Conference on Big Data, Sorrento, Italy, pp. 5408-5417, 2023.[CrossRef] [Google Scholar] [Publisher Link]